Agriculture is a primary activity in many countries,with wheat being a major cereal crop in India.Accurate pre-harvest forecasts of crop acreage and production are critical for policymakers to address supply-demand dy...Agriculture is a primary activity in many countries,with wheat being a major cereal crop in India.Accurate pre-harvest forecasts of crop acreage and production are critical for policymakers to address supply-demand dynamics,pricing,and trade.This study focuses on estimating wheat acreage and yield in Barwala block,Hisar district,Haryana,for the 2019-2020 Rabi season using remote sensing techniques.Multi-temporal satellite data capturing phenological stages of wheat(Seedling to Ripening)were processed using supervised classification with a maximum likelihood classifier in ERDAS Imagine.Wheat crop acreage was determined by overlaying ground truth points on the classified data.The estimated acreage showed a relative deviation of−1.07%compared to statistics from the Department of Agriculture(DoA),Haryana.Yield assessment employed a Semi-Physical model based on the Modified Monteith Model.Key parameters included Photosynthetically Active Radiation(PAR),fraction of PAR absorbed by wheat(fAPAR),light use efficiency,and water stress derived fromthe Land Surface Water Index(LSWI)using Sentinel-2 NIR and SWIR-1 bands.Net Primary Productivity(NPP)was computed for the wheat growth period,and grain yield was estimated using a harvest index obtained fromliterature.The estimated yield had a relative deviation of 9.3% from DoA data.The study demonstrates the potential ofmulti-temporal satellite imagery for accurate block-level wheat acreage and yield estimation,providing a valuable tool for agricultural planning and policy-making.展开更多
文摘Agriculture is a primary activity in many countries,with wheat being a major cereal crop in India.Accurate pre-harvest forecasts of crop acreage and production are critical for policymakers to address supply-demand dynamics,pricing,and trade.This study focuses on estimating wheat acreage and yield in Barwala block,Hisar district,Haryana,for the 2019-2020 Rabi season using remote sensing techniques.Multi-temporal satellite data capturing phenological stages of wheat(Seedling to Ripening)were processed using supervised classification with a maximum likelihood classifier in ERDAS Imagine.Wheat crop acreage was determined by overlaying ground truth points on the classified data.The estimated acreage showed a relative deviation of−1.07%compared to statistics from the Department of Agriculture(DoA),Haryana.Yield assessment employed a Semi-Physical model based on the Modified Monteith Model.Key parameters included Photosynthetically Active Radiation(PAR),fraction of PAR absorbed by wheat(fAPAR),light use efficiency,and water stress derived fromthe Land Surface Water Index(LSWI)using Sentinel-2 NIR and SWIR-1 bands.Net Primary Productivity(NPP)was computed for the wheat growth period,and grain yield was estimated using a harvest index obtained fromliterature.The estimated yield had a relative deviation of 9.3% from DoA data.The study demonstrates the potential ofmulti-temporal satellite imagery for accurate block-level wheat acreage and yield estimation,providing a valuable tool for agricultural planning and policy-making.
